Deep Learning Earth Observation (52 results)
Earth Observation Data Analytics Using Machine and Deep Learning : Modern Tools, Applications and Challenges
Garg, Sanjay (EDT); Jain, Swati (EDT); Dube, Nitant (EDT); Varghese, Nebu (EDT)
Language: English
Published by The Institution of Engineering and Technology 2023
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Language: English
Published by Institution of Engineering and Technology, GB 2023
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Hardback. Condition: New. Earth Observation Data Analytics Using Machine and Deep Learning: Modern tools, applications and challenges covers the basic properties, features and models for Earth observation (EO) recorded by very high-resolution (VHR) multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-temporal…observations. Approaches for applying pre-processing methods and deep learning techniques to satellite images for various applications - such as identifying land cover features, object detection, crop classification, target recognition, and the monitoring of earth resources - are described. Cost-efficient resource allocation solutions are provided, which are robust against common uncertainties that occur in annotating and extracting features on satellite images. This book is a valuable resource for engineers and researchers in academia and industry working on AI, machine and deep learning, data science, remote sensing, GIS, SAR, satellite communications, space science, image processing and computer vision. It will also be of interest to staff at research agencies, lecturers and advanced students in related fields. Readers will need a basic understanding of computing, remote sensing, GIS and image interpretation.
Earth Observation Data Analytics Using Machine and Deep Learning : Modern Tools, Applications and Challenges
Garg, Sanjay (EDT); Jain, Swati (EDT); Dube, Nitant (EDT); Varghese, Nebu (EDT)
Language: English
Published by The Institution of Engineering and Technology 2023
- Hardcover
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Taschenbuch. Condition: Neu. Applications of Deep Learning to Radar Polarimetry | A Physics First Approach to Machine Learning in Radar Earth Observation Applications | Shaunak de | Taschenbuch | 212 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139815999 | Verantwortliche Person für die EU: preigu GmbH & Co.…KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Earth Observation Data Analytics Using Machine and Deep Learning : Modern Tools, Applications and Challenges
Garg, Sanjay (EDT); Jain, Swati (EDT); Dube, Nitant (EDT); Varghese, Nebu (EDT)
Language: English
Published by The Institution of Engineering and Technology 2023
- Hardcover
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Earth Observation Data Analytics Using Machine and Deep Learning : Modern Tools, Applications and Challenges
Garg, Sanjay (EDT); Jain, Swati (EDT); Dube, Nitant (EDT); Varghese, Nebu (EDT)
Language: English
Published by The Institution of Engineering and Technology 2023
- Hardcover
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Language: English
Published by The Institution of Engineering and Technology 2023
- Hardcover
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Language: English
Published by Institution of Engineering and Technology, GB 2023
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Hardback. Condition: New. Earth Observation Data Analytics Using Machine and Deep Learning: Modern tools, applications and challenges covers the basic properties, features and models for Earth observation (EO) recorded by very high-resolution (VHR) multispectral, hyperspectral, synthetic aperture radar (SAR), and multi-temporal…observations. Approaches for applying pre-processing methods and deep learning techniques to satellite images for various applications - such as identifying land cover features, object detection, crop classification, target recognition, and the monitoring of earth resources - are described. Cost-efficient resource allocation solutions are provided, which are robust against common uncertainties that occur in annotating and extracting features on satellite images. This book is a valuable resource for engineers and researchers in academia and industry working on AI, machine and deep learning, data science, remote sensing, GIS, SAR, satellite communications, space science, image processing and computer vision. It will also be of interest to staff at research agencies, lecturers and advanced students in related fields. Readers will need a basic understanding of computing, remote sensing, GIS and image interpretation.
Earth Observation Data Analytics Using Machine and Deep Learning: Modern Tools, Applications and Challenges
Garg, Sanjay (Editor)/ Jain, Swati (Editor)/ Dube, Nitant (Editor)/ Varghese, Nebu (Editor)
- Hardcover
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Deep Learning for Earth Observation and Climate Monitoring
Bhatti, Uzair Aslam (EDT); Nizamani, Mir Muhammad (EDT); Wang, Yong (EDT); Tang, Hao (EDT)
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Deep Learning for Earth Observation and Climate Monitoring
Bhatti, Uzair Aslam (EDT); Nizamani, Mir Muhammad (EDT); Wang, Yong (EDT); Tang, Hao (EDT)
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Deep Learning for Earth Observation and Climate Monitoring
Bhatti, Uzair Aslam (EDT); Nizamani, Mir Muhammad (EDT); Wang, Yong (EDT); Tang, Hao (EDT)
- Softcover
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Deep Learning for Earth Observation and Climate Monitoring
Bhatti, Uzair Aslam (EDT); Nizamani, Mir Muhammad (EDT); Wang, Yong (EDT); Tang, Hao (EDT)
- Softcover
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Condition: New. Introduces deep learning for classification, covering recent improvements in image segmentation and encoding priors, anomaly detection and target recognition, and domain adaptabilityIncludes both learning representations and unsupervised de.
Language: English
Published by Institution Of Engineering & Technology Jul 2023 2023
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: Neu. Neuware - Using machine and deep learning techniques the authors introduce pre-processing methods applied to satellite images to identify land cover features, detect object, classify crops, recognize targets, and monitor and support earth resources. Readers will need a basic understanding of computing, remo…te sensing and image interpretation.
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Taschenbuch. Condition: Neu. Neuware - Deep Learning for Multi-Sensor Earth Observation addresses the need for transformative Deep Learning techniques to navigate the complexity of multi-sensor data fusion. With insights drawn from the frontiers of remote sensing technology and AI advancements, it covers the potential of fusing…data of varying spatial, spectral, and temporal dimensions from both active and passive sensors. This book offers a concise, yet comprehensive, resource, addressing the challenges of data integration and uncertainty quantification from foundational concepts to advanced applications. Case studies illustrate the practicality of deep learning techniques, while cutting-edge approaches such as self-supervised learning, graph neural networks, and foundation models chart a course for future development.Structured for clarity, the book builds upon its own concepts, leading readers through introductory explanations, sensor-specific insights, and ultimately to advanced concepts and specialized applications. By bridging the gap between theory and practice, this volume equips researchers, geoscientists, and enthusiasts with the knowledge to reshape Earth observation through the dynamic lens of deep learning.
Language: English
Published by Elsevier - Health Sciences Division Jun 2025 2025
- Softcover
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Taschenbuch. Condition: Neu. Neuware - Deep Learning for Earth Observation and Climate Monitoring bridges the gap between deep learning and the Earth sciences, offering cutting-edge techniques and applications that are transforming our understanding of the environment. With a focus on practical scenarios, this book introduces re…aders to the fundamental concepts of deep learning, from classification and image segmentation to anomaly detection and domain adaptability. The book includes practical discussion on regression, parameter retrieval, forecasting, and interpolation, among other topics. With a solid foundational theory, real-world examples, and example codes, it provides a full understanding of how intelligent systems can be applied to enhance Earth observation and especially climate monitoring.This book allows readers to apply learning representations, unsupervised deep learning, and physics-aware models to Earth observation data, enabling them to leverage the power of deep learning to fully utilize the wealth of environmental data from satellite technologies.
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- Softcover
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Radar remote sensing has made significant technological and scientific advances in the past few years. Sensors and constellations are able to acquire high resolution, polarimetric, wide swath data with high temporal repetivity. This has…lead to an exponential increase in the volume of data available. With more temporally dense constellations planned in the near future, it is imperative that automated techniques based on machine learning algorithms be developed that are able to take advantage of all the acquired data and convert latent information to actionable knowledge. However, the use of indiscriminate machine learning techniques can be problematic since there is no guarantee that the learned model makes sense from a physical standpoint. Advanced neural network techniques, collectively called 'deep leaning' algorithms have demonstrated the ability to self-learn features from a data-volume, greatly reducing the need for time-consuming feature tuning. In this book, novel deep learning algorithms and architectures are detailed for various earth observation applications using fully polarimetric SAR data based, and constrained by the principles of scattering physics.
